Precise Recognition of Blurred Chinese Characters by
Considering Change in Distribution
Shin'ichiro Omachi, Fang Sun, and Hirotomo Aso
Proceedings of The 10th Scandinavian Conference on Image Analysis (SCIA'97),
pp.501-506, June 1997
In this paper, a new algorithm for Chinese character recognition
This method has an especial effect on character images those are not clear.
Comparing with a clear character image, a blurred character image always
has a big change in shape that makes the recognition more difficult.
In order to recognize blurred characters precisely, the concept of
degree of blur is employed.
We also investigate how the distribution
of feature vectors changes if a part of character image is crashed.
Since the degree of blur is calculated from each sub-area of
character image, the condition of the image can be described clearly.
The distribution can be reconstructed to respond to the change
expressed by the degree of blur.
The method proposed in this paper can recognize blurred characters
precisely by modifying the Mahalanobis distance function according to
change in distribution.
The effectiveness of the new method is shown by experiments
with blurred character images.